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For any large or mid-sized organization to survive in today’s highly competitive market, its decision makers require intelligible information to gauge key metrics affecting various business strategies effectively. They heavily rely on Business Intelligence (BI) solutions to drive innovation and agility for meeting the constantly changing consumer demand.
Data Warehouses serve as a core component of any BI project. They are pivotal to collecting data from disparate sources and extracting actionable insights to provide a clearer picture for better decision making. However, with fast evolving business requirements, Data Warehouses must be able to work with a wide range of data sources and offer concrete solutions with the ability to support quick iterations, bridging the lack of agility that traditional ETL tools entail. This is where Data Warehouse Automation (DWA) steps in.
Why DWA is Essential for BI Projects
Working with an enterprise-level Data Warehouse generally requires overlooking and coordinating various systems, databases, and applications across the organization. Users are required to carefully manage factors, such as timing, sequence, and conditions, affecting different aspects of a BI project. A single misstep can lead to wasted time and resources, potentially resulting in bad data.
In addition, the traditional data collation techniques from simple dashboard and reporting systems take weeks, if not months, to accumulate and analyze data to feed into BI tools. Just preparing data to transform into information can consume more than half of the project resources, leaving business users overloaded when it comes to working with the other aspects of BI project life cycle.
How DWA can Streamline BI Project Implementation
Whether you are implementing a BI Architecture with a standard reporting system, an OLAP product, or a data mining functionality, Data Warehouse Automation can help speed up several aspects of your project, such as:
Automate Major Data Warehouse Activities
DWA allows businesses to optimize and automate different areas of a Data Warehouse. From designing models and developing the source system to creating ETL jobs and testing out the documentation, you can perform such critical tasks using tried and tested design patterns and best practices. This leads to lowered costs, higher Data Quality, reduced risks, and improved productivity, all at the expense of fewer resources.
Enhance Implementation Speed
When DWA is integrated into the BI project lifecycle, it significantly changes the way a business perceives Data Warehouses. Traditionally, a great emphasis was put on getting the entire setup right the first time, for which comprehensive design analysis and modeling was performed. With Data Warehouse Automation, you can perform fast and frequent development of ETL functions and apply quick updates. This also goes extremely well with agile development practices, as well as allow businesses to experience a substantial increase in Data Quality, analysis rapidity, and cost savings.
Perhaps the biggest advantage businesses enjoy with DWA integration is the ability to quickly respond to the changing consumer market dynamics and business conditions. Since DWA offers faster time-to-value, it allows business users to tap into the latest insights from their BI tools and make more accurate, effective decisions related to day-to-day activities. In addition, it helps in integrating new data sources, data profiling and quality management, tracking Data Lineage, and supporting Slowly Changing Dimensions (SCD), making it easier for business users to get maximum value out of their BI strategy.
Luxury to Experiment with Implementation Approaches
DWA enhances Data Analysis speed that allows comparing different implementation approaches and their results, without having to wait weeks or months. It enables users to gather and analyze data from disparate sources, pass it through the BI development cycle, and get results within a matter of days. This would virtually be impossible with a traditional Data Warehouse setup, as the amount of time and resources expended in performing such tests would be high. Data Warehouse Automation provides the ability to run a complete cycle in a short amount of time, allowing you to see the results instantly and fine tune your BI strategy for desired outcomes.
Business users supporting DWA have asserted that using this method in the initial phases of BI implementation can speed up the process by five times. Considering that data volumes have been predicted to increase exponentially in the coming years, DWA can play a massive role in allowing key decision makers to quickly react to changing dimensions of the business landscape.